Abstract

Privacy has been
identified as a hot button issue in literature on Social Network
Sites (SNSs). While considerable research has been conducted with
teenagers and young adults, scant attention has been paid to
differences among adult age groups regarding privacy management
behavior. With a multidimensional approach to privacy attitudes, we
investigate Facebook use, privacy attitudes, online privacy
literacy, disclosure, and privacy protective behavior on Facebook
across three adult age groups (18-40, 41-65, and 65+). The sample
consisted of an online convenience sample of 518 adult Facebook
users. Comparisons suggested that although age groups were
comparable in terms of general Internet use and online privacy
literacy, younger groups were more likely to use SNSs more
frequently, use Facebook for social interaction purposes, and have
larger networks. Also, younger adults were more likely to
self-disclose and engage in privacy protective behaviors on
Facebook. In terms of privacy attitudes, older age groups were more
likely to be concerned about privacy of other individuals. In
general, all dimensions of privacy attitudes (i.e., belief that
privacy is a right, being concerned about one’s privacy, belief
that one’s privacy is contingent on others, being concerned about
protecting privacy of others) were positively correlated with
engagement in privacy protective behavior on Facebook. A mediation
model demonstrated that amount of disclosure mediated the
relationship between age groups and privacy protective behavior on
Facebook. Finally, ANCOVA suggested that the impact of privacy
attitudes on privacy protective behavior was stronger among mature
adults. Also, unlike older age groups, among young adults,
considering privacy as a right or being concerned about privacy of
other individuals had no impact on privacy protective behavior.

Additionally,
given age differences in SNS usage patterns (Van den Broeck et al.,
2015) a comparative analysis of the respective influence of privacy
literacy, attitudes and concerns on privacy management behavior
across different age groups is needed. While extant studies on SNS
use have mainly focused on comparison of adults and adolescents
(e.g., Livingstone, 2008; Peter & Valkenburg, 2011), relatively
less attention has been paid to age differences among different
adult age groups, with some recent exceptions (e.g., Steijin, 2014;
Van den Broeck et al., 2015).

Given
these considerations, this study provides a detailed examination of
privacy related behavior of U.S. adults on Facebook. We engage in a
comparison of three age groups based on the life cycle theory: young
adults (18-40), middle adults (40-65) and mature adults (65+). We
compare these groups in terms of their privacy literacy, privacy
concerns and attitudes, and investigate how these factors predict
their respective self-disclosure and privacy protective behavior on
Facebook.

Privacy Management and SNSs

According
to the Petronio’s Communication Privacy Management (CPM) model
(2002), privacy management, which can be defined as people’s
control over circulation of personal information, comprises
utilization of strategies (also called privacy rules) to control
individual and/or group boundaries. Accordingly, CPM considers
privacy as a dialectical relationship between forces “pulling
between and with the needs of being both private through concealing
and public through revealing” (p.12) and argues that disclosure
and privacy constitute a kind of unity within which both are
necessary for each other. The heightened use of SNS sites for
socialization has led to a growing number of studies that
investigate the two dimensions of privacy management:
self-disclosure and privacy protection (e.g., Joinson et al., 2010;
Walton & Rice, 2013; Walrave et al., 2012; Yang & Tan,
2012).

Extant
research provides inconsistent results regarding the relationship
between self-disclosure and privacy protective behavior as two
dimensions of privacy management. On the one hand, studies suggest
that users may strategically employ these two approaches to
complement each other. For example, Lewis, Kaufman, and Christakis
(2008) reports that among U.S. college students, those who had
private Facebook profiles were more active. On the other hand, some
scholars (e.g. Christofides, Muise, & Desmarais, 2009) suggest
that these two types of privacy management approaches are two
independent behaviors, influenced by distinct factors.

In
general, privacy literacy and attitudes about privacy are two
factors that have received considerable attention as predictors of
privacy management behavior (e.g., boyd & Hargiatti, 2010;
Debatin et al., 2009; Park, 2011). One commonly shared argument has
been that people with higher privacy literacy—comprising
declarative (“knowing that”) and procedural (“knowing how”)
knowledge (Trepte et al. 2015)—are better at protecting their
privacy (e.g., boyd & Hargiatti, 2010). For example, Park (2011)
reports that it is positively associated with online privacy
protective behavior. Within the context of use of SNSs, studies
indicate that having technical skills and familiarity with privacy
settings are positively correlated with changing privacy settings
(boyd & Hargittai, 2010; Debatin et al. 2009). It should also be
noted that, literacy and the accompanying confidence in the ability
to manage one’s privacy may also influence the extent to which
individuals engage in disclosure by reducing what Turow and Hennessy
(2007) name as “fear of disclosure” (p. 305).

Attitudes
about privacy may also determine the extent to which an individual
engages in privacy management behavior in general (Jensen &
Sørensen, 2013; Taddicken, 2014; Van den Broeck et al., 2015;
Vitak, 2012). However, in current literature on SNS and privacy
behavior, there is substantial disagreement about whether privacy
attitudes can predict behavior. For example, the concept of “privacy
paradox”, initially coined by Barnes (2006), has often been used
to refer to a discrepancy between being concerned about privacy and
self-disclosure and likelihood of engaging in privacy protection
(e.g., Acquisti & Gross, 2006, Dienlin & Trepte, 2015,
Taddicken, 2014).

One
potential reason for this discrepancy pertains to the users’
risk-benefit calculation regarding engagement in SNSs. Specifically,
according to the CPM, the decision about level of openness entails a
consideration of the expected benefits, such as self-clarification,
and relationship development, and the potential “perils of
revealing” (Petronio, 2002, p.66). In line with the CPM, what has
been named as the gratifications
hypothesis
(Dienlin & Trepte, 2015; Trepte, Dienlin, & Reinecke, 2014)
argues that while evaluating the risks and benefits of a privacy
related decision (e.g., whether to disclose or not, whether to close
one’s profile to public) users, despite being aware of the risks,
will consider the gratifications to exceed the risks. Hence, the
privacy paradox stems from the fact that as SNSs are increasingly
embedded in individuals’ social lives, self-disclosure becomes
somewhat like a necessity even when such platforms do not afford
adequate privacy protection (Blank, Bolsover, & Dubois, 2014).

According
to Dienlin and Trepte (2015), another reason for the privacy paradox
concerns the attitude-behavior gap. Accordingly, there are two
important problems in existing measurements of privacy attitudes.
First, these measures tend to confound “privacy concerns” with
“privacy attitudes”. Second, there is a mismatch between the
types of behaviors and types of attitudes measured. As Dienlin and
Trepte (2015) note, majority of the studies in this field use “a
multitude of singular behaviors that did not consider the
multidimensional nature of privacy” (p.286). Consequently, they
call for the adoption of approaches that account for the
multidimensionality of privacy.

Multidimensionality
of privacy attitudes becomes even more important to consider in SNS
environments. This is primarily because privacy related behavior in
the context of SNSs does not take place in isolation but involve the
consideration of wider network of others that may be affected by
one’s actions (Baruh & Popescu, 2015; Marwick & boyd,
2014). Indeed, as CPM suggests, privacy management in networked
environments entails sharing of the responsibility in protecting
boundaries.

Based
on these conceptualizations of privacy as a networked and
multidimensional phenomenon, Baruh and Cemalcılar (2014), have
constructed a multidimensional privacy orientation scale that
measures four distinct dimensions of privacy attitudes. This scale
includes measurement of concern about privacy as well as value given
to privacy as: (1) belief in value of privacy as a right (i.e., the
belief that privacy is a fundamental right that needs legal
protection), (2) other-contingent privacy (i.e., the belief that the
level of privacy a person enjoys depends on the extent to which
other people are careful about protecting their own privacy), (3)
concern about own informational privacy (i.e., concern about who has
access to information about oneself, how the information is used),
and (4) concern about privacy of others (i.e., respecting the
privacy of others even when they are not careful about their
privacy). All four of these dimensions of privacy attitudes were
found to be positively correlated with both online privacy
protective behavior in general and privacy protective behavior on
Facebook on a sample of US adult users (Mean age 45.7).

In
line with the gratifications hypothesis and the CPM, in their recent
study, Van der Broeck et al. (2015) argue that given the differences
in frequency and type of SNS use across different age groups,
privacy related behavior on SNSs may also vary as a function of age.
Hence, a comparative analysis that focuses on age differences in
relation to privacy attitudes, concerns, privacy literacy,
self-disclosure behavior, and privacy protective measures taken
within the context of SNSs is imperative.

Current
research on self-disclosure and privacy-related behavior has
primarily focused on adolescents and children (Van den Broeck et
al., 2015). There is only limited data available on the effect of
age on SNS use in general (Chang, Choi, Bazarova, & Löckenhoff,
2015) and privacy management behavior in SNSs particularly (Steijn,
2014). Below, we first summarize extant research on age differences
in SNS usage patterns and then focus on age differences related to
disclosure, privacy attitudes and privacy management behavior.

Lifestages and Differences in
Self-Disclosure and Privacy

Over
the span of the last decade, SNS usage has become commonplace among
all adult populations. According to a 2015 report published by Pew
Research Center, while only 7% of all adults in the U.S. were SNS
users a decade ago, in 2015 this number increased to 65%. Ninety
percent of young adults are currently SNS users and usage among
those who are 65 years old or older has tripled since 2010, reaching
to 35% (Perrin, 2015).

Research
based on life cycle theory (Erikson, 1968) has shown that
individuals’ expectations from and preference about interpersonal
relationships vary depending on the life stage they are at. Major
life events (e.g., school, employment, marriage, retirement) play a
critical role in individuals’ motivations and behavioral patterns
regarding social relations (Holmes & Rahe, 1967). Recent
meta-analytic work indicates that life stages influence both the
structure and the size of individuals’ social networks. Namely,
individuals’ network size reaches a peak by early young adulthood,
after which the size plateaus until late young adulthood and then
starts continuous decrease thereafter (Wrzus, Hanel, Wagner, &
Neyer, 2013). Socio-emotional selective theory is proposed as a
framework to interpret this change in social network size.
Accordingly, while informational goals are related to expansion of
one’s networks in younger adulthood, as individuals age, they tend
to focus on close relationships to satisfy their emotional needs,
resulting in elimination of peripheral relations (Wrzus et al,
2013).

In
line with the life cycle theory, recent research demonstrates key
differences across adult age groups in the types of uses of SNSs.
Older users primarily use SNSs to maintain their relationship with
close contacts (i.e., friends and family) and overall spend less
time on the site (e.g., Brandtzæg, Lüders, & Skjetne, 2010;
Christofides, Muise, & Desmarais, 2012; McAndrew & Jeong,
2012), whereas younger adults seek larger and more heterogeneous
social networks and use SNSs for a wider range of purposes (Arjan,
Pfeil, & Zaphiris, 2008; Chang et al., 2015). Being at a
developmental stage characterized by “exploration and instability”
(Arnett, 2004), young adults are more likely to be motivated to
experiment with social boundaries and engage in self-disclosure on
SNSs as a means of satisfying this motivation than older adults do
(for a summary, see Van den Broeck et al., 2015). Relatedly, young
adults are more likely to use SNSs for self-presentation, which, in
turn, may be related to their tendency to use SNSs more actively,
which entails higher self-disclosure (Arjan et al., 2008; Chang et
al., 2015; Christofides et al., 2012; Peter & Valkenburg, 2011;
Steijn, 2014; Walrave et al., 2012). Given these findings, this
study will test the following two hypotheses:

H1. Younger adults
a) will have larger network of friends on Facebook and b) will be
more likely to engage in uses of Facebook that are oriented towards
social interactions with others.

H2. Younger adults
will be more likely to engage in self-disclosure on Facebook.

With
respect to age differences regarding privacy protective behavior,
extant research points to a similar trend. Across different SNS
platforms like Facebook and Google+, age of adult users has been
found to be inversely related to the frequency with which users
checked and/or changed their privacy settings (Blank et al. 2014;
Van den Broeck et al. 2015) and their tendency to take measures to
limit the circulation of information about themselves such as
untagging photos and limiting updates to certain people (Litt,
2013).

H3. Younger adults
will be more likely to adopt privacy protective behavior on
Facebook.

Research
also suggests that privacy literacy may be an important factor that
explains the observed age differences regarding the adoption of
privacy protection measures in SNS settings. Accordingly, because
they are more tech savvy in general and because they tend to use
SNSs more frequently, younger adults may not only have higher
awareness of privacy risks posed by SNSs but may also be more apt in
adjusting privacy settings to protect themselves from these risks
(Bolton et al., 2013; boyd & Hargittai, 2010; Brandtzæg et al.,
2010; Debatin et al., 2009; Litt, 2013; Tufekçi, 2012). In line
with these findings, Van den Broeck et al. (2015) report significant
age differences in knowledge of options for changing Facebook
privacy settings.

Yet,
evidence also suggests that age differences in privacy literacy may
not be as pronounced as assumed (Hoofnagle, King, Li, & Turow,
2010). Indeed, according to a recent study by Blank et al. (2014),
there were no significant differences between age and skills
associated with changing privacy settings. As such, it is possible
that the any age difference with respect to knowledge of Facebook
privacy settings may be a function of perceived need for changing
privacy settings rather than a gap in literacy. Namely, to the
extent that older adults—as illustrated in previous research
summarized above—are less frequent users of SNSs and are less
likely to engage in disclosure of information on such platforms,
they may not perceive a need for changing their privacy settings.
This could, in turn, decrease their knowledge of options (Maaß,
2011; Urista, Dong, & Day, 2009; Van den Broeck et al., 2015)
simply because they did not perceive the need to try the options.

In
the light of this discussion regarding potential age differences in
engaging in privacy protective behavior and the respective roles
that self-disclosure (as a factor that influences need for privacy
protection) and literacy may play, and due to the inconsistencies in
findings from extant research, we pursue the following research
question:

RQ1. What is the
respective role that disclosure and privacy literacy play as factors
that mediate the relationship between user age group and privacy
protective behavior?

Regarding
the relationship between privacy attitudes and privacy management in
general, an area of inquiry that has received significant amount of
attention concerns differences between adults and adolescents. These
studies have reported key differences between adults and adolescents
as to what is considered as (disclosure of) “private”
information and what constitutes a breach of privacy (e.g.,
Livingstone, 2008; Livingstone, Ólafsson, & Staksrud, 2011;
Peter & Valkenburg, 2011). In terms of age differences in
privacy attitudes among adults, current research provides some
conflicting evidence. On the one hand, several studies indicate that
privacy concerns are present across different age groups (e.g.,
Jensen & Sørensen, 2013; Taddicken, 2014). On the other hand, a
number of recent studies report that older adults are more likely to
be concerned about privacy, which, accordingly, can be attributed to
the fact that younger adults are more comfortable about managing
their privacy and hence do not feel as concerned (Maaß, 2011;
Tufekçi, 2012; Van Broeck et al. 2015).

It
should also be noted that the studies discussed in the previous
paragraph primarily focus on age differences about privacy concerns
without differentiating concerns from attitudes. Yet, despite the
aforementioned importance of understanding the behavioral
implications of the multidimensionality of privacy attitudes, there
is a considerable dearth of research on age differences pertaining
privacy attitudes in general and how privacy attitudes may interact
with age in predicting SNS users’ tendency to engage in privacy
protective behavior.

The
CPM provides a useful point of entry for understanding the nature of
this potential interaction between privacy attitudes and age.
According to CPM, in addition to factors such as risk-benefit ratio
and motivational criteria, one important factor that influences
privacy rule development concerns cultural differences that may
govern individuals’ expectations and values (Petronio, 2002).
Consider, for example, discussions in privacy literature tracing
how, particularly over the last two decades, privacy is being
transformed from being a right into a commodity (e.g., Davies, 1997;
Papacharissi, 2010). Accordingly, along with this recent
transformation of privacy into being a commodity, neoliberal
approaches to privacy protection place the onus on individuals to
understand risks and act (Solove, 2013). To our knowledge, there is
no empirical research on how these changes are implicated in age
differences in understanding of privacy mirroring these cultural
differences in values and expectations. Yet, it is possible that for
young adults, who have grown within this cultural context, concern
about individual privacy will be more important in predicting
behavior than other considerations related to the value of privacy
as a right or respect for the privacy of other individuals. Given
these considerations, we investigate the following questions
regarding age differences in privacy attitudes and how age may
interact with different dimensions of privacy attitudes in
predicting the extent to which an individual engages in privacy
protective behavior:

RQ2. What are the
differences between age groups in terms of different dimensions of
privacy attitudes?

RQ3. How does age
interact with different dimensions of privacy attitudes in
predicting privacy protective behavior on Facebook?

Method

Participants

The
sample comprised a convenience sample of adult online panel members
provided by Qualtrics Panel from ClearVoice Research®. The
ClearVoice research participation is voluntary. Panel members are
recruited and regularly verified via SMS or phone. Out of the 1540
panel members who received the invitation for the survey, 600
completed it (completion rate 39%). Out of the 600 respondents, 518
reported using Facebook. The study will mainly focus on these
respondents. The respondents were between the ages of 18 and 85
(53.3% female, Mage
= 49.36, SDage
= 13.83). Participants received cash or gift cards from Qualtrics.

For
the comparative analyses, we divided the participants into three age
groups based on lifespan stages (Kail & Cavanaugh, 2010): young
adulthood (18-40 years old, n
= 138, 41.3% female), middle adulthood (41-65 years old, n
= 330, 57.9% female), and late adulthood (65+ years old, n
= 50, 56% female). Age groups were comparable in terms of their
educational level (23-31% were high school graduates or less, and
67% in each group had some college education or were college
graduates). A significantly larger proportion of young adults (97%)
reported using Facebook than middle adulthood (84%) and late
adulthood groups (81%).

Measures

Facebook
uses and gratifications. To
compare groups in terms of their motivations for using Facebook, we
collected data about four types of uses of Facebook based on prior
research, all measured with three items using 5-point Likert scale
ranging from 0 to 4 (Chen, 2011; Whiting, & Williams, 2013): (1)
using Facebook to satisfy social curiosity (e.g., “to learn about
daily lives of other people”, α = .85, M
= 1.44, SD
= 0.97), (2) using Facebook for getting information (e.g., “to be
up to date about current events”, α = .90, M
= 2.11, SD
= 1.04), (3) using Facebook for social interaction (e.g., “to
expand my circle”, α = .87, M
= 1.65, SD
= 1.05), and (4) using Facebook for entertainment (e.g., “to have
fun”, α = .89, M
= 2.63, SD
= 0.92). Items were averaged to create an index score for each
subscale, respectively.

Information
disclosure behavior on Facebook. Information
disclosure behavior on Facebook was measured using eight items
ranging from never
(0) to more
than once a day
(5) (M
= .79, SD
= 0.84). A general score for information disclosure on Facebook was
calculated by averaging the items. See Appendix A for wording of the
items.

Online
privacy literacy.
Eight true-false items were used to assess respondents’ general
knowledge about online privacy. See Appendix B for wording of the
items. A literacy score was calculated by summing the number of
correct answers (M
= 5.66, SD
= 1.45, range: 1-8).

Multidimensional
privacy orientation scale. Participants
filled out the 18-item Multidimensional Privacy Orientation Scale
(Baruh & Cemalcılar, 2014), using a five-point scale ranging
from 1 (strongly
disagree)
to 5 (strongly
agree).
The dimensions of the scale were as follows: 1) Privacy
as a right;
2) Concern
about own informational privacy,
(3) Other-contingent
privacy,
4) Concern
about privacy of others.
Table 1 provides the wording and the factor loading of items in each
dimension, and the reliability and descriptive summaries of ensuing
dimensions of privacy attitudes.

Privacy
protective measures on Facebook. Use
of privacy protective measures on Facebook was assessed by summing
11 items based on Baruh and Cemalcılar (2014) and Litt (2013),
measuring whether the participant ever engaged in specific types of
privacy protective actions on Facebook (M
= 4.42, SD
= 3.08, range: 0-11). See Appendix C for wording of the items. Also,
Appendix D demonstrates correlations among and descriptive summaries
of the variables.

Table
1. Components
of the Privacy Orientation Scale.

Factors

1

2

3

4

Factor
1: Privacy as a right

Privacy
laws should be strengthened to protect personal privacy

.78

.21

.14

.24

People
need legal protection against misuse of personal data

.85

.13

.11

.28

If
I were to write a constitution today, I would probably add
privacy as a fundamental right

.85

.13

.11

.28

Factor
2: Concern about own informational privacy

When
I share the details of my personal life with somebody, I often
worry that he/she will tell those details to other people

.10

.80

.18

.04

I
am concerned that people around me know too much about me

.08

.84

.10

-.05

I
am concerned with the consequences of sharing identity
information

.25

.67

.28

.24

I
worry about sharing information with more people than I intend
to

.16

.77

.25

.18

Factor
3: Other-contingent privacy

If
somebody is not careful about protecting their own privacy, I
cannot trust them about respecting mine

.09

.15

.79

.23

If
I am to enjoy some privacy in my life, I need my friends to be
careful about protecting their privacy as well

.14

.21

.78

.25

I
could never trust someone as my confidant if they go around
sharing details about their own private lives

.06

.16

.81

.12

The
level of privacy that I can enjoy depends on the extent to which
people around me protect their own privacy

.13

.25

.79

.08

Factor
4: Concern about privacy of others

It
is important for me to respect the privacy of individuals, even
if they are not careful about protecting their own privacy

.24

.08

.22

.73

I
value other people’s privacy as much as I value mine

.15

.09

.15

.80

Even
when somebody is not careful about his/her privacy, I do my best
to respect that person’s privacy

.20

.08

.10

.84

I
always do my best not to intrude into other people’s private
lives

.16

.03

.13

.75

Respect
for others’ privacy should be an important priority in social
relations

.27

.10

.16

.81

Cronbach’s
α

.83

.83

.86

.88

Mean

4.14

3.47

3.46

4.15

Standard
Deviation

.73

.89

.84

.63

Note:
For each subscale, the Cronbach’s α values are calculated using
the items with factor loadings indicated in bold.

In
addition to these key measures related to our main hypotheses and
research questions, to further assess age differences in SNS use, we
collected data regarding Internet and Social Media use. Respondents
reported the number of years they had been using the Internet, their
daily Internet use separately for work days and weekends. In terms
of SNS use and SNS network, respondents reported the frequency of
their use of various social media platforms (Facebook, Twitter,
video sharing platforms like YouTube, and photo sharing platforms
like Instagram) using a scale ranging from never
(0) to more
than once a day
(5) and the number of friends on their Facebook account and
percentage of Facebook friends with whom they never met in person.

Results

Table
2 provides a comparison of the age groups in terms of level of
Internet use, use of social media, and characteristics of
respondents’ Facebook friends network and uses and gratifications
of Facebook. Overall, there was no significant difference between
age groups in terms years of internet use, F(2,
510) = 0.348, p
> .05 and hours per day of internet use during weekdays Welch’s
F(2,
135.80) = 2.576, p
> .05; however, mature adults reported using the Internet less
frequently during the weekends than younger age groups Welch’s
F(2,
130.14) = 9.659, p
< .001.

Table
2. Comparison
of Age Groups in Terms of Internet and SNS Use.

Young
Adulthood

Middle
Adulthood

Mature
Adulthood

F

η2
(ω2)

Internet
Use

Years
of Internet use

8.26
(2.46)

8.44
(2.47)

8.23
(2.36)

.348NS

.001

Internet
hours per work day3

4.49
(2.93)

4.57
(2.87)

3.75
(2.31)

2.576NS

.006

Internet
hours per weekend day3

5.18
(2.91)a

5.42
(2.77)a

3.77
(2.40)b

9.659

.033

Social
Media (Frequency)

Facebook3

4.29
(1.13)a

4.05
(1.28)b

3.56
(1.47)b

5.543

.017

Twitter3

1.46
(1.95)a

.74
(1.35)b

.29
(.74)c

1.449

.063

Photo
Share3

1.42
(1.54)a

.58
(.93)b

.35
(.97)b

20.300

.069

Video
Share3

2.61
(1.68)a

1.67
(1.33)b

1.10
(1.30)c

24.523

.083

Facebook
Network

Number
of Friends1,
3

250.63
(229.69)a

205.82
(218.72)a

117.08
(159.91)b

9.697

.034

Percent
of Facebook friends not met in person (mean percent)2,
3

29.85
(30.70)

36.05
(34.08)

35.31
(33.39)

1.850NS

.003

FB
Uses and Gratifications

Entertainment

2.64
(.92)

2.67
(.90)

2.36
(1.07)

2.411NS

.009

Social
interaction

1.84
(1.08)a

1.62
(1.02)a,b

1.27
(1.01)b

5.793

.022

Social
curiosity

1.77
(1.04)a

1.34
(.91)b

1.21
(.92)b

11.527

.043

Information
seeking

2.22
(1.09)

2.23
(1.00)

2.03
(1.16)

.823NS

.003

Notes:
Sample n’s for the age groups vary as follows depending on
missing values in specific variables: Young Adulthood: n
= 131 to 138; Middle Adulthood: n
= 319 to 330; Mature Adulthood: n
= 48 to 50. All F
values other than with a superscript of NS are significant at p
<.05 level. Different superscripts in a row denote columns that
are significantly different. Unless otherwise stated (see below at
Note 3), Bonferroni post-hoc analysis was used for group
comparisons. 1
Capped to 700, 90th percentile. 2
Capped to 90%, 90th percentile.3
ANOVA’s for variables violating the homogeneity of variances
assumption were conducted using Welch’s F
was
used. For these variables adjusted Omega-squared (ω2) was used for
effect size. Also, for these variables post-hoc analysis for group
comparisons were conducted using the Games-Howell procedure instead
of the Bonferroni procedure.

Age Group Differences in
Facebook Use, Disclosure and Privacy Protection on Facebook

As
predicted by Hypothesis 1, age groups differed on the extent of
Facebook network size, with number of friends decreasing by age
groups Welch’s F(2,
134.78) = 9.687, p
< .001. Yet, there was no difference in terms of percentage of
friends that respondents characterized as not having met in person
(on average one in three, for all groups) Welch’s F(2,
126.41) = 1.850, p
> .05. Also in line with Hypothesis 1, young adults were more
likely than older age groups to utilize Facebook for social
interaction purposes F(2,
518) = 5.793, p < .01 and satisfying social curiosity F(2,
518) = 11.527, p
< .01. On the other hand, age groups did not significantly differ
from each other in terms of use of Facebook to get information about
current events and for using Facebook because it is entertaining
(Table 2).

Table
3 compares age groups in terms of disclosure on Facebook, number of
privacy protective measures taken on Facebook, online privacy
literacy, and privacy attitudes. One-way analysis of variance
results showed that, age groups were significantly different from
each other in terms of both disclosure on Facebook Welch’s F(2,
132.81) = 19.729, p
< .001 and use of privacy protection measures on Facebook, F(2,
515) = 15.222, p
< .001, confirming H2 and H3, respectively. Post-hoc analyses
indicated that young adults were significantly more likely than
older age groups to disclose information and engage in privacy
protective behavior on Facebook.

Notes:
Sample n’s for the age groups vary as follows depending on
missing values in specific variables: Young Adulthood: n
= 137 to 138; Middle Adulthood: n
= 329 to 330; Mature Adulthood: n
= 50. All F
values other than with a superscript of NS are significant at p
<.05 level. Different superscripts in a row denote columns that
are significantly different. Unless otherwise stated (see below at
Note 1), Bonferroni post-hoc analysis was used for group
comparisons. 1
ANOVA’s for variables violating the homogeneity of variances
assumption were conducted using Welch’s F
was used. For these variables adjusted Omega-squared (ω2) was used
for effect size. Also, for these variables post-hoc analysis for
group comparisons were conducted using the Games-Howell procedure
instead of the Bonferroni procedure.

Privacy Literacy and
Disclosure as Predictors of Privacy Protection on Facebook

The
RQ1 inquired about the respective roles that online privacy literacy
and disclosure may play as factors that mediate the relationship
between age groups and utilization of privacy protective measures on
Facebook. Since differences among age groups in terms of online
privacy literacy was not significant, F(2,
516) = 1.601, p
> .05 (Table 3), the mediation analysis will focus only on
whether disclosure on Facebook mediates the relationship between age
groups and number of privacy protective measures taken on Facebook.
To test this mediation model, we used the PROCESS macro in SPSS
(Model 4, with a bootstrap approach of 5000 drawings). This model
allows for a sequential comparison of the effects of a
multicategorical independent variable (in this analysis, three age
groups) on mediating and dependent variables (Hayes & Preacher,
2014). Specifically, in this sequential analysis, initially the
first group (young adulthood) is compared with all the remaining
groups combined (middle adulthood and mature adulthood), then the
first two groups (young adulthood and middle adulthood) are compared
with the mature adults.

Figure
1 provides the summary of the mediation analysis. Accordingly,
information disclosure partially mediated the relationship between
age groups and privacy management. Specifically, young adults were
more likely than both of the older age groups (B
= -0.50, p
< .001) and mature adults were less likely than both of the
younger age groups (B
= -0.25, p
< .05) to engage in information disclosure on Facebook. In turn,
those who disclosed more were more likely to take privacy protective
measures on Facebook (B
= .56, p
< .01). In addition, after controlling for disclosure, young
adults were more likely than other age groups to utilize privacy
protection measures (B
= -1.15, p
< .01). The model explained 16% of the variance in privacy
protection measures (p
< .001).

Age Differences in Privacy
Attitudes and Their Impact on Privacy Protection on Facebook

RQ2
inquired about whether there would be differences between age groups
in terms of different dimensions of privacy attitudes and the
respective impact of the attitudes on privacy protective behavior.
Table 3 provides the comparison of age groups with respect to the
four dimensions of privacy attitudes. Accordingly, there were no
significant differences among age groups for the belief that privacy
is a right, F(2,
518) = 0.966, p
> .05 and concern about one’s own privacy, F(2,
518) = 0.816, p
> .05. On the other hand, age groups significantly differed from
each other in terms the belief that their own privacy is contingent
on the extent to which other people around them are careful about
protecting their own privacy (other-contingent privacy), Welch’s
F(2,
134.54) = 13.125, p
< .001 and in terms of valuing the privacy of others, F(2,
517) = 6.115, p
< .01. Specifically, older adult groups were most likely to think
that their own privacy depended on whether other people around them
would safeguard their privacy. They were followed by middle age
adults and then young adults. Also, young adults were less likely
than both other age groups to report valuing privacy of others.

As
shown in Figure 2, a similar trend is observed for all four of the
privacy attitude dimensions. Namely, among members of the mature
adulthood groups, the impact of privacy attitudes on use of measures
to protect privacy on Facebook is generally stronger than other age
groups. The only attitude dimension for which young adults and
mature adults were comparable to each other in terms of the impact
of the attitude on number of privacy protective measures taken on
Facebook was “concern about one’s own informational privacy”
(Figure 2B). Indeed, among young adults, belief in privacy as right
(B
= .506, p
= .119, Figure 2A) and concern about privacy of others (B
= .068, p
= .848, Figure 2D) had no impact on number of measures taken to
protect privacy on FB.

Figure
2.
A) Interaction between age groups and valuing privacy “as a
right”; B) Interaction between age groups and concern about one’s
own informational privacy; C) Interaction between age groups and
other contingent privacy; D) Interaction between age groups and
concern about privacy of others.

Discussion

In
recent years, informational privacy has become a hot button issue in
literature on SNSs (Wilson, Gosling, & Graham, 2012). Previous
studies have mainly focused on two dimensions of privacy management
behavior: self-disclosure and taking privacy protecting measures.
Considering that SNSs are increasingly being used by adults of all
ages (Perrin, 2015) and given the recent evidence suggesting that
older adults differ from younger adults and adolescents in terms of
how they use SNSs (e.g., Brandtzæg et al., 2010; Chang et al.,
2015; McAndrew & Jeong, 2012), understanding age differences in
relation to privacy related behavior is an important subject of
inquiry. Yet, until recently, there has been very limited research
in this area (for recent exceptions see, Steijn, 2014; Van den
Broeck et al., 2015).

Accordingly,
in this study we investigated how adult age groups—divided based
on three lifespan stages (young adulthood, 18 to 40 years old;
middle adulthood, 41 to 65 years old; and mature adulthood, 65+
years old)—differ from each other in terms of online literacy,
privacy concerns and attitudes, self-disclosure and privacy
protective behavior on Facebook. Also, we investigated how
disclosure mediates the relationship between age and use of privacy
protection measures on Facebook. Finally, we report findings
regarding the interaction between age group membership and privacy
attitude dimensions as predictors of privacy protection on Facebook.

Consistent
with previous research (e.g., Chang et al., 2015; Steijn, 2014; Van
den Broeck et al., 2015), our findings indicate that older adults
are less likely to disclose information and that they are less
likely to employ privacy protection on Facebook. This may be
attributed to age differences in frequency of and motivations in use
of Facebook. Namely, studies indicate that older adults not only
spend less time on Facebook but also are less motivated to use SNSs
for purposes—such as expanding one’s network or engaging in
self-presentation—that may be associated with self-disclosure
(e.g., Chang et al., 2015; Peter & Valkenburg, 2011; Steijn,
2014; Walrave et al., 2012). Our analyses of Facebook usage amount
and motivations are in line with previous research. Not only did
frequency of use of Facebook (and indeed other social media
platforms like Twitter) declined with age, but also, older age
groups had smaller networks and were less likely to use Facebook for
socialization purposes (i.e., satisfying social curiosity and
engaging in social interactions).

Previous
literature offers two alternative explanations for the observed
differences between age groups in terms of utilization of privacy
protection measures on Facebook. On the one hand, one interpretation
that is frequently offered is that users from younger generations
are more likely to employ privacy protection measures because they
are both more aware of the privacy risks and more technically apt in
changing privacy settings (e.g., Bolton et al., 2013; Debatin et
al., 2009; Tufekçi, 2012). On the other hand, it is also possible
that older adults do not perceive as strong a need for utilizing
these measures as younger adults do. The results summarized in this
study are in line with this second interpretation of age group
differences. First, we did not find any significant differences
between age groups in terms of general online privacy literacy. When
combined with the finding that across all age groups online privacy
literacy is not related to use of privacy protection on Facebook
this finding may imply that increasing literacy will not be
sufficient in terms of boosting protective behavior. Second, among
potential predictors, information disclosure had the highest
correlation with privacy protection on Facebook. Third, the
mediation model we tested indicates that information disclosure
mediates the relationship between age and privacy protection.

To
our knowledge, this study constitutes one of the first attempts at
understanding age group differences in privacy attitudes as a
multidimensional construct and how they may influence privacy
protective behavior. Specifically, we focused on four potential
dimensions of privacy attitudes proposed by Baruh and Cemalcılar
(2014): 1) concern about one’s own privacy; 2) belief that privacy
constitutes a value that should be legally safeguarded; 3)
codependency of privacy (i.e., belief that one’s privacy depends
on how careful others are about their own privacy); 4) concern about
privacy of others (i.e., respecting others’ privacy).

Our
analyses of these four dimensions of privacy attitudes reveal
several important insights. First, while all dimensions of privacy
attitudes are positively related to adoption of privacy protection
measures on Facebook, none of them were significantly related to
disclosure behavior. Second, there were no significant differences
between age groups in terms of considering privacy as a right or
being concerned about own privacy. However, we observed that older
adults were more likely to be conscious about the co-dependency of
privacy and to value privacy of others. This finding becomes
particularly important in the light of results concerning how
privacy attitudes and age interact with each other in predicting use
of privacy protective measures on Facebook. Specifically, our
findings indicate that for all of the dimensions of privacy
attitudes, the impact of the attitudes on use of privacy protective
measures is strongest for mature adults. Perhaps more importantly,
our analysis indicates that among younger adults, consideration of
the value of privacy as a fundamental right and respect for the
privacy of others do not significantly predict use of privacy
protective measures on Facebook. We believe that these results can
be interpreted through the premise of the CPM that cultural values
play an important role in privacy rulemaking (Petronio, 2002).
Hence, the ‘neoliberal’ reconceptualization of privacy as a
personal responsibility may explain the age differences we are
observing.

Another
potential explanation to be considered is that Facebook usage
patterns may make privacy attitude dimensions less relevant for
younger users. That is, given the findings that younger adults are
more likely to seek wider networks and utilize Facebook for
socialization purposes, which include sharing information and
perusing information from others, it is likely that concern about
privacy of others will not factor into their privacy rulemaking
decisions. On the other hand, as life cycle theory suggests, since
the network of older adults are more likely to contain close rather
than peripheral relations, they are more likely to value the privacy
of the members of their network.

Limitations and Future
Research

While
interpreting these findings, it should be noted that the data for
this study came from a convenience sample of online panel of
respondents who opted in for receiving survey invites and
responding. As such, particularly in terms of privacy concerns, this
group of respondents may not be representative of Facebook users in
general. Relatedly, as reported above, while majority of respondents
across all age groups reported using Facebook, mature adults were
slightly less likely to be Facebook users than younger age groups, a
factor that may potentially bias results about the relationship
between privacy attitudes and privacy protection behavior. Also, the
fact that we used a convenience sample of online respondents means
that we did not have much control over the size of the age groups
that were compared, resulting in disproportionate sizes for age
groups.

Another
key factor to consider concerns the level of specificity of some of
the measures utilized in the study. First, rather than measuring
attitudes about privacy within the context of Facebook, the
multidimensional privacy scale administered in this study is a
general measure of privacy attitudes. Studies on attitude-behavior
relationship indicate that low correlations between attitudes and
behavior may often be the result of such mismatch between level of
specificity of attitudes and behavior (Ajzen, 2001; Glasman &
Albarracin, 2006). As such, this may explain the statistically
significant yet small correlations (ranging between r = .12 and r =
.27) between the dimensions of privacy attitudes and privacy
protective measures taken on Facebook. However, it should also be
noted that despite this potential specificity problem, all
dimensions of privacy attitudes were strongly related to adoption of
privacy protective behavior on Facebook among mature adults.
Nevertheless, future research shall consider applications of the
different dimensions of the privacy scale to the context of specific
SNS platforms or other online consumption behaviors.

In
a similar vein, the privacy literacy items utilized for this study
focused on declarative (i.e., “knowing that”) knowledge
regarding general online privacy rather than procedural knowledge
(i.e., “knowing how”) of Facebook privacy protective behavior.
This may explain why literacy was not related to privacy protective
behavior and had a very low correlation with disclosure. An
important reason why we focused on declarative knowledge as a
predictor of privacy protective behavior concerns the potential
circularity of the relationship between them. Indeed, recent
research (Bartsch & Dienlin, 2016) provides reasons to call into
question the direction of causality between previous experience in
privacy protective behavior and procedural knowledge of how to do
so. Still, analysis of the respective influence of declarative and
procedural knowledge on privacy protective behavior would be
valuable in future research, particularly if studied longitudinally
or in controlled experiments that may help test this causal
mechanism.

Relatedly,
a more nuanced measurement of privacy management techniques that
distinguishes between methods that may protect users’ information
from other members of their network and methods that users may
utilize to protect their data from use by the SNS platform would be
useful in terms of understanding age differences.

While
we focused on Facebook because it is among the most commonly used
SNS platforms, recent studies indicate that SNS platforms vary
significantly in terms of the affordances they create for selective
management of information sharing activities (Bazarova & Choi,
2014). Further research may investigate how differences in these
affordances may influence the relationship between age, disclosure
and use of privacy protective measures.

Implications

Despite
these limitations, the findings presented in this study have
important implications both on a conceptual level and in terms of
enhancing privacy risk awareness in ways that can boost protective
behavior. On a conceptual level, the findings regarding the
relationship between different dimensions of privacy attitudes and
use of privacy protective measures on Facebook confirm the arguments
that in a networked age, understanding the relationship between
privacy attitudes and behavior requires that the multidimensionality
of the attitudes is accounted for (Dienlin & Trepte, 2015;
Marwick & boyd, 2014). At the same time, results regarding the
age differences in the impact of privacy attitudes on protective
behavior point to an alternative approach to raising privacy
awareness. That is, within the context of SNSs, as CPM suggests and
our findings confirm, emphasis on the need to engage in privacy
management collectively by the users could be a useful strategy in
raising risk awareness. This could be particularly appealing to
mature adults who are reportedly more cognizant of the co-dependency
of privacy entitlements.

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Appendices

Appendix A – Information
Disclosure on Facebook

0
= Never 1 = Less than once a week 2 = Once a week 3 =
Several times a week 4 = Once a day 5 = More than once a day

1.
____ Write or post photos/videos about what you did in your spare
time? 2. ____ Write or post photos/videos about your family and
friends? 3. ____ Write or post photos/videos about your work or
education? 4. ____ Write or share articles/pictures/videos about
your political views? 5. ____ Write or share
articles/pictures/videos about your religious beliefs? 6. ____
Post photos/videos of yourself or your friends in party, drinking
with friends? 7. ____ Share information about your location? 8.
____ Write about your feelings or emotions?

Appendix B – Online Privacy
Literacy

Below
there are a few statements about Internet and online privacy. For
each statement, please indicate whether you think it is true or
false

1
= Yes 2 = No

Table B1. Online
Privacy Literacy: The Distribution of Answers.

Item

Correct
Answer

(%)

False
Answer

(%)

Companies
today have the ability to place an online advertisement that
targets you based on information collected on your web-browsing
behavior

95.2

4.8

A
company can tell that you have opened an email even if you do
not respond

22.8

77.2

When
you go to a website, it can collect information about you even
if you do not register

15.1

84.9

Popular
search engine sites, such as Google, track the sites you come
from and go to

5.8

94.2

When
a website has a privacy policy, it means the site will not share
your information with other websites or companies

50.8

49.2

Government
policy restricts how long websites can keep the information they
gather about you

26.8

73.2

It
is legal for an online store to charge different people
different prices at the same time of day

50.9

49.1

When
I give personal information to an online banking site, privacy
laws say the site has no right to share that information, even
with companies it owns

59.2

40.8

Appendix C – Privacy
Protective Measures Taken on Facebook

Have
you ever done the following because
you are concerned about your privacy on Facebook?

1=
Yes 2= No

1.
____ Untagged photos/videos on Facebook because you were concerned
about privacy 2. ____ Delete information from your Facebook
profile or timeline because you were concerned about privacy 3.
____ Unfriend people on Facebook you were concerned about privacy
4. ____ Deactivate your Facebook profile 5. ____ Restrict
access to parts of your Facebook profile so that only your friends
can see them 6. ____ Make your status updates private and allow
only your friends to see them 7. ____ Turn off automatic face
recognition on Facebook 8. ____ Remove an app from your Facebook
account because of the information it collects about you. 9.
____ Restrict the types of information that you share with apps on
Facebook 10. ____ Turn of all apps on Facebook 11. ____
Install an additional application to prevent third parties on
Facebook from tracking you and displaying targeted advertisements.

Appendix
D – Correlations among and Descriptive Summaries of Variables